Online transaction processing (OLTP) systems support high transaction-oriented applications. The workload of OLTP entails frequent updates that each involves modifications to relatively small amounts database data and entails execution of many queries that each access and generate relatively small amounts of data. Important capabilities of the clustered database systems supporting OLTP workloads include not only high availability but also transaction processing of database data. While these capabilities are important to supporting OLTP workloads, the capabilities exact high overhead.
The database data generated by OLTP can be exploited by decision support systems (DSS). DSS generates analytic data from raw database data, such as that generated by OLTP systems. The workload of DSS entails execution of queries requiring much computation and accessing a large volume of data.
Under database consolidation, OLTP systems and DSS may be hosted on the same clustered database system. Database consolidation not only allows for more efficient use of computer resources but also provides a DSS system better access to the raw database data generated by the OLTP system. However, the DSS work load is subjected to the overhead needed by OLTP to support high availability and transaction processing, which impairs the scalability of clustered database systems used for consolidating OLTP and DSS systems.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.